Physical Sciences and Mathematics Commons^™

Smoke Detection In Videos Using Non-Redundant Local Binary Pattern-Based Features, Hongda Tian, Wanqing Li, Philip Ogunbona, Duc Thanh Nguyen, Ce Zhan

Professor Philip Ogunbona

This paper presents a novel and low complexity method for real-time video-based smoke detection. As a local texture operator, Non-Redundant Local Binary Pattern (NRLBP) is more discriminative and robust to illumination changes in comparison with original Local Binary Pattern (LBP), thus is employed to encode the appearance information of smoke. Non-Redundant Local Motion Binary Pattern (NRLMBP), which is computed on the difference image of consecutive frames, is introduced to capture the motion information of smoke. Experimental results show that NRLBP outperforms the original LBP in the smoke detection task. Furthermore, the combination of NRLBP and NRLMBP, which can be considered …

Illumination Invariant Face Detection Using Classifier Fusion, Alister Cordiner, Philip Ogunbona, Wanqing Li

Professor Philip Ogunbona

An approach to the problem of illumination variations in face detection that uses classifier fusion is presented. Multiple face detectors are seperately trained for different illumination environments and their results are combined using a combination rule. To define the illumination environments, the training samples are clustered based on their illumination using unsupervised training. Different methods of clustering the samples and combining the outputs of the classifiers are examined. Experiments with the AR face database show that the proposed method achieves higher accuracy than the traditional monolithic face detection method.

Object Detection Using Non-Redundant Local Binary Patterns, Duc Thanh Nguyen, Zhimin Zong, Philip Ogunbona, Wanqing Li

Professor Philip Ogunbona

Local Binary Pattern (LBP) as a descriptor, has been successfully used in various object recognition tasks because of its discriminative property and computational simplicity. In this paper a variant of the LBP referred to as Non-Redundant Local Binary Pattern (NRLBP) is introduced and its application for object detection is demonstrated. Compared with the original LBP descriptor, the NRLBP has advantage of providing a more compact description of object’s appearance. Furthermore, the NRLBP is more discriminative since it reflects the relative contrast between the background and foreground. The proposed descriptor is employed to encode human’s appearance in a human detection task. …

Preliminary Investigations Of Pigment Responses To Phylloxera Infestation, A L. Blanchfield, K S. Powell, Sharon A. Robinson

Sharon Robinson

Early detection of grape phylloxera (Daktulosphaira vitifoliae) infestation is vital for the implementation of post-outbreak quarantine in Australia. Remote sensing systems exploit changes in leaf pigment content associated with plant stress and offer a real possibility of a phylloxera-specific detection system. Pre-visual, symptomatic changes in the pigment content of phylloxera-infested grapevine leaves were investigated using high performance liquid chromatography (HPLC) as a potential aid to improve current phylloxera detection methods. A glasshouse trial was established to characterize the response of two grapevine varieties, Vitis vinifera ‘Cabernet Sauvignon’ and ‘Shiraz’, to phylloxera infestation, in a controlled environment. Field trials were conducted …

Predicting Disease Outbreaks Using A Support Vector Machine Model, Nicolae Dragu

Senior Theses and Projects

The purpose of this research is to create an efficient way of detecting disease outbreaks from news articles using Support Vector Machines (SVM). An SVM is a supervised machine learning method used for classification and regression problems. The role of the SVM in this project is to “learn” to distinguish between news articles that may indicate a disease outbreak and those that do not.

A series of health-related articles from the World Health Organization is parsed using a Java program in order to create vectors for the SVM. Each such article thus results in a vector. A basic negation detection …

Reaction Of The C2h Radical With 1-Butyne (C4h6): Low Temperature Kinetics And Isomer-Specific Product Detection, Satchin Soorkia, Adam J. Trevitt, Talitha M. Selby, David L. Osborn, Craig A. Taatjes, Kevin R. Wilson, Stephen R. Leone

Adam Trevitt

No abstract provided.

Reactions Of The Cn Radical With Benzene And Toluene: Product Detection And Low-Temperature Kinetics, Adam J. Trevitt, Fabien Goulay, Craig A. Taatjes, David L. Osborn, Stephen R. Leone

Adam Trevitt

Low-temperature rate coefficients are measured for the CN + benzene and CN + toluene reactions using the pulsed Laval nozzle expansion technique coupled with laser-induced fluorescence detection. The CN + benzene reaction rate coefficient at 105, 165, and 295 K is found to be relatively constant over this temperature range, (3.9−4.9) × 10−10 cm3 molecule−1 s−1. These rapid kinetics, along with the observed negligible temperature dependence, are consistent with a barrierless reaction entrance channel and reaction efficiencies approaching unity. The CN + toluene reaction is measured to have a rate coefficient of 1.3 × 10−10 cm3 molecule−1 s−1 at 105 …

A Novel Route To Copper(Ii) Detection Using 'Click' Chemistry-Induced Aggregation Of Gold Nanoparticles, Carol Hua, William H. Zhang, Swahnnya De Almeida, Simone Ciampi, Danmar Gloria, Guozhen Liu, Jason Brian Harper, J Justin Gooding

Australian Institute for Innovative Materials - Papers

A simple colorimetric method for the detection of copper ions in water is described. This method is based on the 'click' copper(i)-catalyzed azide-alkyne cycloaddition reaction and its use in promoting the aggregation of azide-tagged gold nanoparticles by a dialkyne cross-linker is described. Nanoparticle cross-linking, evidenced as a colour change, is used for the detection of copper ions. The lowest detected concentration by the naked eye was 1.8 μM, with the response linear with log(concentration) between 1.8-200 μM. The selectivity relative to other potentially interfering ions was evaluated.

Direct Detection Of Additives And Degradation Products From Polymers By Liquid Extraction Surface Analysis Employing Chip-Based Nanospray Mass Spectrometry, Martin Paine, Phillip Barker, Shane A. Maclaughlin, Todd W. Mitchell, Stephen J. Blanksby

Faculty of Science - Papers (Archive)

Rationale: Polymer-based surface coatings in outdoor applications experience accelerated degradation due to exposure to solar radiation, oxygen and atmospheric pollutants. These deleterious agents cause undesirable changes to the polymers aesthetic and mechanical properties reducing its lifetime. The use of antioxidants such as hindered amine light stabilisers (HALS) retard these degradative processes, however, mechanisms for HALS action and polymer degradation are poorly understood. Methods: Detection of the hindered amine light stabiliser (HALS) TINUVIN®123 (bis (1-octyloxy-2,2,6,6-tetramethyl-4-piperidyl) sebacate) and the polymer degradation products directly from a polyester-based coil coating was achieved by liquid extraction surface analysis (LESA) coupled to a triple quadrupole QTRAP® …

Detecting, Tracking, And Recognizing Activities In Aerial Video, Vladimir Reilly

Electronic Theses and Dissertations

In this dissertation, we address the problem of detecting humans and vehicles, tracking them in crowded scenes, and finally determining their activities in aerial video. Even though this is a well explored problem in the field of computer vision, many challenges still remain when one is presented with realistic data. These challenges include large camera motion, strong scene parallax, fast object motion, large object density, strong shadows, and insufficiently large action datasets. Therefore, we propose a number of novel methods based on exploiting scene constraints from the imagery itself to aid in the detection and tracking of objects. We show, …